29 research outputs found
Optimal global carbon management with ocean sequestration
We investigate the socially optimal intervention in the global carbon cycle. Limiting factors are (i) increasing atmospheric carbon concentration due to fossil fuel-related carbon emissions, and (ii) the inertia of the global carbon cycle itself. Accordingly, we explicitly include the largest non-atmospheric carbon reservoir, the ocean, to achieve a better representation of the global carbon cycle than the proportional-decay assumption usually resorted to in economic models. We also investigate the option to directly inject CO2 into the deep ocean (a form of carbon sequestration), deriving from this a critical level for ocean sequestration costs. Above this level, ocean sequestration is merely a temporary option; below it, ocean sequestration is the long-term option permitting extended use of fossil fuels. The latter alternative involves higher atmospheric stabilization levels. In this connection it should be noted that the efficiency of ocean sequestration depends on the time-preference and the inertia of the carbon cycl
Models on CO2 abatement under uncertainty
The major goal of this thesis is to contribute answering the
question how changes in economic actions affect the climate and at the same time, how do changes in the climate affect the economy.
This thesis consists of three parts. In the first part (Chapter 2) we stress the role of the oceans as a sink for atmospheric carbon by developing a dynamic global carbon cycle model with two reservoirs containing atmosphere and two ocean layers. We consider a special form of carbon capture and storage: The capture of carbon and its sequestration into the deep ocean reservoir. Adding a non-renewable
resource stock we study the socially optimal extraction and carbon capture and storage decision rules. We show that carbon capture and storage accelerates the slow natural flux within the carbon cycle, and because of its temporary abatement character it dampens the overshooting of the atmospheric reservoir. After studying the decentralized economy we show that the optimal carbon tax has an
inverted u-shape. Depending on the initial sizes of the reservoirs and the speed of carbon fluxes between the reservoirs carbon taxes can also be increasing, decreasing or u-shaped. Our model is the first of its kind which can generate this result. Furthermore, we conclude that the level of the carbon tax should be positively adjusted to account for (i) damage uncertainty and (ii) the declining ability of the deep ocean to absorb atmospheric carbon.
In the second part of the thesis (Chapter 3) we apply standardized numerical techniques of stochastic optimization to the climate change issue. We ask the question how the optimal mitigation of climate change evolves if intrinsic uncertainty about damage is inherent to the model. In particular, we are interested in how the effect of uncertainty on climate change mitigation changes with
different levels of risk aversion.
A major finding is that the effects of stochasticity differ even in
sign as to emission control with varying parameters: introduction of
stochasticity may increase or decrease emission control depending on
the specific parameter setting. Our analysis covers a large range of
the parameter space, in particular the degree of risk aversion and
the level of uncertainty. We identify regions of the state space for
which higher levels of uncertainty or risk aversion result in
different policy rules for emission control. Similarly, given a
certain state of the world we conclude that the effect of
uncertainty on emission control changes (in level and sign) with the
degree of risk aversion. In other words, uncertainties in climatic
trends may induce people's precautionary emission reduction but also
may drive away money from abatement.
In the third part of the thesis (Chapter 4) we are interested in how
a capital stock which is linked to a polluting technology is
maintained, accumulated and utilized optimally. In order to analyze
the inter- and intra-sectoral tradeoffs between capacity building
and capacity using which guide the economy's transition process
towards a balanced growth equilibrium we develop a model with two
production sectors that generate a homogenous consumption good. The
production processes in these two sectors differ with respect to the
technology which is used. While in one sector the process is clean,
generating output in the other sector also creates environmental
damage. The technologies are completely embedded in the
corresponding stock of physical capital. Hence, the application of
one technology can only be intensified by investing more in the
associated capital stock or utilizing it more intensively.
Our findings show that the combination of heterogeneous capital,
endogenous depreciation and capital intensity is essential for
extracting qualitative and quantitative implications for policy
makers about the easiness of a technology switch. If the economic
environment requires a change in the energy portfolio, an economy
driven by our model structure can not react without severe time
lags, due to the ex post clay nature of investment. Installation of
the desired capital stock simply takes time if we do not want to
abstain from smooth consumption patterns. In a next step we
introduce a stock of carbon which is subject to uncertainty. With
this modification we can investigate how uncertainty about damage
resulting from climate change influences the optimal interplay
between capacity building and capacity utilization in a more
realistic environment. We conclude that increasing uncertainty
intensifies the need for a rapid build-up of the clean capital
stock. It also reduces the demand for effective capital services
associated with the polluting technology
Climate change mitigation and ecosystem services : A stochastic analysis
Degradation of ecosystem services may be a major component of climate change damage, and incorporation of this factor could significantly alter the significance of uncertainty in climate-economy modeling. However, this aspect has been little investigated by economic analyses of climate change and uncertainty. We apply standardized numerical techniques of stochastic optimization to this research question. The model results show that the effects of uncertainty are different with different levels of agent’s risk aversion. Also, uncertainty exhibits different effects on mitigation policy and capital investment according to the availability of ecosystem services. Importantly, both the risk aversion and the availability of ecosystem services can change the effects of uncertainty on mitigation not only in level but also in sign. In other words, mitigation could both increase and decrease with climatic uncertainty. The model would provide hints for policymaking in finding a balance between economic growth, climate protection, and the conservation of ecosystemsclimate change, decision making under uncertainty, stochastic control, renewable resource, ecosystem services
The Optimal Transfer of Capital and Embodied Technologies to Developing Countries
We study the North-South diffusion of technologies embodied in internationally mobile capital in a framework of intertemporal global welfare maximization. Convergence of the growth rates of technical change in the North and South always occurs in the long-run. However, the degree to which the North-South technology gap can be narrowed depends crucially on the level of the absorptive capacity (human capital, infrastructure, legal framework, etc.) in the South. Performing own innovations in the South narrows the technology gap only in the short-run. An optimal development policy requires more capital to be allocated to the South in earlier stages of development. Allowing for optimal investment into the absorptive capacity, the absorptive capacity rises steadily with the aim to close the technology gap completely. Our results show that an optimal development policy requires FDI to be matched by investment into the absorptive capacityTechnology diffusion, technology transfer, capital mobility, FDI, human capital, absorptive capacity
Risk-averse mitigation decisions in an unpredictable climate system
Risk aversion plays a central role in the decisions made in the face of uncertainties, and climate-change mitigation should be no exception. However, the interlinkage of risk aversion and climate-change uncertainties has hardly been investigated numerically, in part because of the computational difficulties of stochastic optimization. In this paper, we apply the numerical techniques of stochastic optimization to the economic modeling of climate change, with the aim of modeling the decision preferences of a risk-conscious agent in the face of unpredictable climate change. The model underlines the critical role played by the risk-aversion parameter in determining the effects of uncertainties on mitigation, not only in level but also in sign
Socially optimal north-south capital transfer and technology diffusion
We study North–South capital transfer and the diffusion of embodied technologies within a framework of intertemporal global welfare maximization. We show saddle path stability and characterize the steady state. We then examine the transition path by running numerical experiments based on realistic data. As a result, technology diffusion will succeed if the absorptive capacity is sufficient which requires sufficient investment. While a large share of capital is allocated to the South in early periods, this share declines in later periods when the South has caught up in terms of technologies
The effect of uncertainty on decision making about climate change mitigation. A numerical approach of stochastic control
We apply standardized numerical techniques of stochastic optimization (Judd [1998]) to the climate change issue. The model captures the feature that the effects of uncertainty are different with different levels of agent's risk aversion. A major finding is that the effects of stochasticity differ even in sign as to emission control with varying parameters: introduction of stochasticity may increase or decrease emission control depending on parameter settings, in other words, uncertainties of climatic trends may induce people's precautionary emission reduction but also may drive away money from abatementclimate change and uncertainties, stochastic control, climate policy